Although long life tends to run in families, genetics has far less influence on life span than previously estimated, according to a new analysis published in GENETICS. Ruby et al. used a data set of over 400 million historical persons obtained from public pedigrees on Ancestry.com to estimate the heritability of life span, finding it to be well below 10%.

“We can potentially learn many things about the biology of aging from human genetics, but if the heritability of life span is low it tempers our expectations about what types of things we can learn and how easy it will be,” says lead author Graham Ruby (Calico Life Sciences). “It helps contextualize the questions that scientists studying aging can effectively ask.”

Calico Life Sciences is a research and development company whose mission is to understand the fundamental science of aging. So how did Calico get involved with Ancestry, the online genealogy resource?

“We wanted to get a sense for the contribution of genetics to life span, and that’s something you can study using pedigrees,” says Ruby. With millions of members, Ancestry has no shortage of pedigrees.

Fortuitously, researchers at Calico and Ancestry were connected from their time in academic basic research. Calico’s Chief Scientific Officer David Botstein and Ancestry’s Chief Scientific Officer Catherine Ball (senior author on the GENETICS paper) both have backgrounds in yeast research. They were involved in the Saccharomyces Genome Database project during their times at Stanford University and published a number of papers together.

So researchers from both companies teamed up to use publicly available pedigree data from Ancestry.com to approach the problem of figuring out the genetic contributions to human longevity.

“Partnering with Ancestry allowed this new study to gain deeper insights by using a much larger data set than any previous studies of longevity,” says Ball.

The heritability of life span has been well investigated in the literature, with previous estimates ranging around 15-30%.

But some of these studies found that it wasn’t just blood relatives who shared similar life spans—so did spouses. This suggested that the heritability estimates might have been confounded by shared environments or assortative mating (the tendency to choose mates who have similar traits to ourselves).

The new study had the power to investigate these possibilities in more detail because of the large size and high quality of the data. The data set, called the SAP for “set of aggregated and anonymized pedigrees,” was constructed from Ancestry.com pedigrees with the help of source references like birth certificates.

Starting from 54 million subscriber-generated public family trees representing six billion ancestors, Ancestry removed redundant entries and those from people who were still living, stitching the remaining pedigrees together. Before sharing the data with the Calico research team, Ancestry stripped away all identifiable information from the pedigrees, leaving only the year of birth, year of death, place of birth (to the resolution of state within the US and country outside the US), and familial connections that make up the tree structure itself.

The SAP included almost 500 million individuals (with a single pedigree accounting for over 400 million people), largely Americans of European descent, each connected to another by either a parent-child or a spouse-spouse relationship. The scale of the data allowed the researchers to get accurate heritability estimates across different contexts; they could stratify the data by birth cohort or by sex or by other variables without losing the power needed for their analyses. They employed structural equation modeling—a technique that hasn’t often been applied to this problem due to the amount of data required for it to be productive—to calculate life span correlations and heritability across the giant pedigree.

Running the numbers, the team initially found heritability estimates to be between 15-30%—similar to the reported literature.

“But then I did correlations between first cousins-in-law, and their life spans didn’t correlate as much—but it was close,” says Ruby.

When a trait correlates between in-laws similarly to blood relatives, that can mean that something besides genetics is being shared across households. The term heritability describes the proportion of trait variability in a population that can be attributed to genetic differences. But genetics aren’t the only thing that can be passed down between generations: sociocultural factors can also influence certain traits, and these too can be inherited. The combination of genetic heritability and sociocultural heritability is the total transferred variance, that is, the total amount of variability in a trait that can be explained by inheritance.

“The comparison between in-law relatives is something that hadn’t been as thoroughly explored in the prior literature. With this large dataset, we could look at in-law relatives at a large scale and be confident that they weren’t that far off from blood relatives,” says Ruby.

The scale of the data allowed Ruby and colleagues to look not only at siblings-in-law and first cousins-in-law but also to examine correlation in both types of co-siblings-in-law (your sibling’s spouse’s sibling or your spouse’s sibling’s spouse). None of these relationship types generally share household environments, and yet their life spans showed correlation.

If they don’t share genetic information and they don’t share household environment, what accounts for the similarity in life span between individuals within these relationship types? Going back to their impressive dataset, the researchers were able to perform analyses that detected assortative mating.

“What assortative mating means here is that the factors that are important for life span tend to be very similar between mates,” says Ruby. In other words, people tend to select partners with traits like their own—in this case, how long they live.

Of course, you can’t easily guess the longevity of a potential mate. “Generally, people get married before either one of them has died,” jokes Ruby. Because you can’t tell someone’s life span in advance, assortative mating in humans must be based on other characteristics.

The basis of this mate choice could be genetic or sociocultural—or both. For a non-genetic example, if income influences life span, and wealthy people tend to marry other wealthy people, that would lead to correlated longevity. The same would occur for traits more controlled by genetics: if, for example, tall people prefer tall spouses, and height is correlated in some way with how long you live, this would also inflate estimates of life span heritability.

By correcting for these effects of assortative mating, the new analysis found life span heritability is likely no more than seven percent, perhaps even lower.

The upshot? How long you live has less to do with your genes than you might think.

[…] to be very similar between mates,” said lead author Graham Ruby of Calico Life Sciences, in a statement. That means that people tend to choose partners with traits similar to their own — in this case, […]

[…] Researchers looked at data from 400 million people born in the 1800s and early 1900s and found that less than 10% of the variation in longevity can be attributed to genetic differences. Assortative mating — the fact that people tend to select partners with traits like their own […]